Rice: Unconventional Wisdom
Thesis Defense
Graduate and Postdoctoral Studies
Applied Physics
Electrical and Computer Engineering
Speaker: Yun Li
Masters Candidate

  Model-Based Acquisition for Compressive Sensing & Imaging
Tuesday, April 9, 2013
10:00 AM  to 12:00 PM
A227  Abercrombie Engineering Laboratory

Compressive Sensing (CS) is a novel imaging technology based on the inherent redundancy of natural scenes. CS's applications in imaging or classification embodied in the Rice single-pixel camera are limited by its acquisition time. In this study, hybrid-subspace sparse sampling and secant projection on manifold data are applied to speed up imaging and classification tasks. Both methods considerably decrease the number of required measurements compared with the pure random patterns, and make CS applicable in the situation where quick acquisition is required.


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